This project will address how sexting (the exchange of sexually suggestive texts or pictures via mobile phone) and problematic alcohol use together increase the risk for [risky sexual behavior and sexual] assault among college women. My integrated causal path model includes (a) impulsivity-related personality traits - sensation seeking and negative urgency - and (b) learned expectations about alcohol use and sexual activity, both of which are related to alcohol use, sexting, [risky sexual behavior,] and sexual assault (e.g., Corbin et al., 2001; Dir et al., [2013a, under review; Dir & Cyders, under review]). Although supported by cross-sectional data (Dir et al., [2013a]), research has yet to examine my integrated causal model in a prospective framework. The proposed project will be two-fold: (1) A longitudinal analysis of college women's behaviors over two semesters of college (as previously done: F31, PI: Cyders 2006-2009), and (2) an experimental analysis of male and female college students' interpretations of sexting encounters. In order to test my integrative and prospective model of alcohol use and [risky sexual behavior, and sexual] assault risk, I will use multiple methods of assessment (combining self-report data, vignettes, daily diary reports, and text message phone review). The main study hypotheses are: (1) Sexting mediates the relationship between alcohol use and [both risky sexual behavior and] sexual assault among college women (Study 1); (2) Impulsivity-related traits and sex-related alcohol expectancies prospectively predict alcohol use, and subsequent sexting, [risky sexual behavior, and sexual] assault among college women (Study 1); and (3) Males and females differentially interpret implicit messages in sexting and alcohol use behaviors, leading to increased risk for sexual assault (Study 2). Given the high prevalence of mobile phone and alcohol use among college women, models integrating these factors in predicting [risky sexual behavior and sexual] assault are needed in order to effectively intervene on this high-risk group. Successfully demonstrating this risk model would advance research in the field and inform the development of more effective intervention and prevention strategies, including mobile phone-based prevention techniques.